Prediction of Pregnancy-Associated Hypertension Using a Scoring System: A Multicenter Cohort Study

Area of Science:

• Obstetrics and Gynecology
• Cardiovascular Health in Pregnancy
• Perinatal Medicine

Background:

• Pregnancy-associated hypertension (PAH) poses significant risks to maternal and fetal health.
• Accurate early risk prediction is crucial for timely intervention and improved outcomes.
• Existing risk assessment models may lack sufficient predictive power.

Purpose of the Study:

• To develop and validate an early pregnancy risk scoring model for predicting pregnancy-associated hypertension (PAH) and preterm PAH.
• To compare the performance of different models incorporating pre-pregnancy factors, mean arterial pressure (MAP), and PAPP-A.
• To identify optimal predictors for PAH risk stratification.

Main Methods:

• Retrospective analysis of perinatal databases from seven hospitals (January 2009 - December 2020).
• Development and comparison of three risk scoring models (pre-pregnancy factors only, adding MAP, adding MAP and PAPP-A) against the ACOG risk model.
• Data randomly divided into training (70%) and testing (30%) sets; analysis of total and restricted populations (excluding aspirin users).

Main Results:

• A total of 2840 (8.11%) women developed PAH and 1550 (3.3%) developed preterm PAH.
• Models incorporating MAP (Model 2) and MAP with PAPP-A (Model 3) showed superior performance (AUC > 0.82) compared to pre-pregnancy factors alone (AUC ~0.75) and the ACOG model (AUC ~0.66).
• The final scoring system using Model 2 demonstrated moderate to good predictive performance (AUCs 0.78-0.79) in the test set.

Conclusions:

• A risk scoring model integrating pre-pregnancy factors and mean arterial pressure (MAP) offers moderate to high performance for predicting PAH and preterm PAH.
• This model provides a valuable tool for early risk identification in pregnant individuals.
• Further prospective validation studies, potentially including biomarkers and uterine artery Doppler, are warranted.